First insight into the phylogeny of fine‐leaved Festuca in the Altai Mountain Country based on genome‐wide genotyping

Abstract Festuca is one of the largest genera within the Poaceae family. Molecular phylogenies demonstrate that Festuca s.l. comprises two groups: broad‐ and fine‐leaved species. The latter is the species‐richest and taxonomically complicated group due to being paraphyletic. Here, we provide the first insight into the phylogeny of 17 fine‐leaved species of Altai fescues. Based on genome‐wide genotyping, the examined taxa were divided into three markedly differentiated clusters. The first cluster comprises species from the F. rubra complex, the second cluster includes the F. brachyphylla complex, and the third cluster contains taxa from the groups F. ovina, F. valesiaca, and F. kryloviana. Importantly, we detected a complex genetic pattern within the groups of F. valesiaca and F. kryloviana. Moreover, our findings underline a discrepancy between morphological and molecular data for some species distributed within the Altai Mountain Country. We suggest that in order to validate the current findings on the fine‐leaved fescues, additional comprehensive research including morphological, karyological, and molecular methods is required. Nonetheless, our work provides a baseline for further investigations on the genus and studies on the floral diversity of Asia.

Festuca ovina s.l. is considered to have four or more ploidy levels (2n, 4n, 6n, 8n or less 3n, 5n or 7n; Qiu et al., 2021). In Central Asia, the species was divided into two subspecies that later were raised to the rank of species: diploid F. ovina and tetraploid F. sphagnicola B. Keller (Enushchenko & Probatova, 2020). Unfortunately, there are still a lot of species of fescues with unknown ploidy levels, for instance, Festuca borissii Reverd., F. kurtschumica Alexeev, F. kuprijanovii Chusovljanov, and F. saurica Alexeev. Interspecific hybridization is another quite frequent phenomenon that is observed in fine-leaved fescues and plays an important role in species formation within the genus Festuca (Ardenghi et al., 2011;Bednarska, 2009;Bednarska & Brazauskas, 2017;Gutiérrez Villarías et al., 1992). The taxonomical difficulties in Festuca are the result of the morphological similarity of species, and the identification of hybrids based on morphological and anatomical characters is very hard, especially in complexes of closely related and morphologically similar taxa. Thus, molecular and karyological data are currently the only reliable means for identifying species and detecting gene flow (Chusovlyanov & Kotukhov, 2006;Šmarda & Kočí, 2003;Tzvelev & Probatova, 2019).
Currently, new high-throughput techniques such as RADseq, GBS, and DArTseq have provided a solid tool to solve complex taxonomic problems related to hybridization and genetic variation in many wild plant genera (Baiakhmetov et al., 2021;Davey & Blaxter, 2010;Xu et al., 2017).
In this study, we aim to (1) assess genetic structure within fineleaved fescues of the AMC using a genome-wide genotyping technique, (2) evaluate whether hybridization occurs between the taxa, and (3) discuss morphological and anatomical characters of these species.

| Plant material
We analyzed 17 species of 19 Festuca from the AMC. Two taxa, F. lenensis and F. pseudosulcata, are not presented in the study due to the lack of well-preserved herbarium material. A total of 72 samples were either collected in the field or obtained from herbarium materials preserved at ALTB, KRA, KUZ, LE, and TK. Herbaria acronyms used follow Thiers (2021, continuously updated http://sweet gum.nybg.org/ih/). A complete list of taxa and voucher information can be found in Appendix A. All samples were studied by the authors. The specimens were identified according to the multiple keys (Alexeev, 1990;Darbyshire & Pavlick, 2007;Lu et al., 2006;Skvortzov, 1964;Tzvelev, 1976;Tzvelev & Probatova, 2019

| DNA extraction, amplification, and DArT sequencing
Isolation of genomic DNA followed by genome complexity reduction using restriction enzymes and high-throughput polymorphism detection (Kilian et al., 2012) were performed by Diversity Arrays Technology Pty Ltd. The resulting single nucleotide polymorphisms (SNPs) were processed in the R-package dartR v.1.9.4 (Gruber et al., 2021) with the following parameters: (1) a scoring reproducibility of 100%; (2) SNP loci with read depth <5 or >50 were removed; (3) at least 95% loci called (the respective DNA fragment had been identified in greater than 95% of all individuals); (4) monomorphic loci were removed; and (5) SNPs that shared secondaries (had more than one sequence tag represented in the dataset) were randomly filtered out to keep only one random sequence tag. Subsequently, three approaches were used to analyze the genetic structure: (1) Unweighted Pair Group Method with Arithmetic Mean (UPGMA); (2) fastSTRUCTURE and STRUCTURE analyses; and (3) Principal Coordinates Analysis (PCoA). UPGMA cluster analyses based on the Hamming Distance with 1000 bootstrap replicates were performed in the R-package poppr v.2.9.1 (Kamvar et al., 2014(Kamvar et al., , 2015. The final UPGMA trees were visualized via iTOL v.6.3.2 (Letunic & Bork, 2021). Next, the genetic structure was investigated using fast- The output matrix for the best K-value was plotted using the R package pophelperShiny v.2.1.0 (Francis, 2017). Additionally, to assess genetic structure at the level of particular clusters inferred with the UPGMA and fastSTRUCTURE, we used STRUCTURE v.2.3.4 (Pritchard et al., 2000) via StrAuto v.1.0 (Chhatre & Emerson, 2017).
Ten replicate runs were performed for each number of clusters (K) from one to five/10 with a burn-in of 10,000 iterations followed by 100,000 MCMC iterations. The optimal K-value was identified based on Evanno's method of delta K statistics (Evanno et al., 2005) as implemented in Structure Harvester (Earl & von Holdt, 2012). The calculation of average proportions of membership across all runs was performed with Clumpak via StructureSelector, while the R package pophelperShiny was used to visualize the output matrices. We applied the threshold of 0.10 < q < 0.90 as the most widely utilized measure for the assessment of hybridization (Winkler et al., 2011) with q-values >0.9 being pure species and 0.45 < q < 0.55 being F1 hybrids, while first-and second-generation backcrosses with one parent were considered at q-values 0.25 and 0.125, respectively (Beugin et al., 2018). Then, PCoAs on a Euclidean distance matrix were performed using the R-package dartR and visualized with gg-plot2 v.3.3.0 (Wickham, 2016) to show the first two components and plotly v.4.9.2 (Sievert et al., 2021) to illustrate the first three components.
Moreover, to verify whether each inferred Cluster can be differentiated further, we performed additional analyses using UPGMA,  Subcluster C that was analyzed with 3516 SNPs includes six alpine and mountain-steppe species (Figure 7). There was no correlation between the results of molecular analyses and the geographical location of the populations (Figure 7e). The STRUCTURE analysis revealed the most likely number of K value of 4, while the UPGMA disclosed three major clades (Figure 7b). The results of the UPGMA were also supported by PCoA (Figure 7c).
The first three axes of the PCoA explained 19.2%, 16.1%, and 11.2% of the total genetic divergence within the studied group.
Following the PCoA, specimens were grouped into three markedly differentiated groups corresponding to pure genotypes of F. rubra, F. brevissima, and F. brachyphylla) had been analyzed using a few loci, and the remaining 14 had not been investigated molecularly. This lack of data prevented a clear understanding of the relationships between these species within the genus. Genomewide SNP genotyping is an informative and accurate method used to analyze relationships within taxonomically complicated taxa. It is successfully applied to the study of natural hybridization in the wild (Baiakhmetov et al., 2020(Baiakhmetov et al., , 2021 strawberry (Bassil et al., 2015). Our molecular data provided the information that allowed us to review the value of morphological characters in AMC fescue species. Furthermore, we have a detailed discussion about the correspondence between molecular and morphological data.

| Clade composition and morphological traits
Our findings clearly demonstrate that the studied individuals can be grouped into three clusters. Cluster I includes two species, F. rubra and F. richardsonii, both belonging to the section Aulaxyper. Festuca richardsonii was a questionable species that was provided from the AMC and occurs at an altitude of 3000 m (Alexeev, 1990;Chusovljanov, 2007). Although the analyses revealed the specimens ALTB62 and ALTB63 formed separate well-supported genetic groups, we presume that this is an indication of genetic variability at the population level, as supported by the low delta k value. Morphologically, the ALTB62 and ALTB63 specimens are distinguished from F. rubra by the lemma length, the awn length, and the lemma pubescence (Alexeev, 1990;Tzvelev, 1976;Tzvelev & Probatova, 2019). Furthermore, specimens of F. richardsonii from the Arctic and the AMC differ by the culm length 50-60 versus 10-30(−40) cm; the shape of the panicle open versus contracted; the number of spikelets on the lower panicle branches 2 or more versus 1-2 spikelets, and the awn length 1-2.3 versus 0-1(−1.5) mm, respectively. The specimens of F. richardsonii from the AMC belong to F. rubra; however, due to the latter species being extremely polymorphic, further comprehensive taxonomical revision is required.
Cluster II includes the samples of F. brachyphylla and F. brevissima, both from the section Festuca. These two species differ from the other Altai fescues by having shorter anthers, 0.5-1.5 versus 1.5-3 mm, respectively. The UPGMA, STRUCTURE, and PCoA confirm a strong genetic differentiation between these taxa.
Morphologically, these species are easily distinguishable by the number of spikelets in the panicle <8 versus >11 spikelets, the number of spikelets on the lower branches 1-2 versus 2 and more spikelets, the panicle length 0.7-26 versus 23-55 mm, the lemma length 2.5-4 versus 4.5-5.5 mm, and the plant length up to 12 versus 10-55 cm. It is worth noticing that F. brevissima is a new record to the Altai Mountains and currently it is the southernmost locality within the species range. Also, F. brevissima is morphologically similar to another arctic species, F. edlundiae. However, they differ by, for example, the length and shape of сulms, the shape of glumes, and the number of chromosomes 2n = 2x = 14 versus 2n = 4x = 28 (Darbyshire & Pavlick, 2007).
Within Cluster III, Subcluster A includes specimens representing F. kuprijanovii, F. ovina, and F. sphagnicola characterized by a welldefined midrib and a continuous sclerenchyma layer. Festuca kuprijanovii is an endemic species known only from the Altai Republic (Chusovljanov, 1998). It is closely related to F. sphagnicola and F.  (Alexeev, 1990;Šmarda & Kočí, 2003). Thus, due to molecular markers being used for the first time to delimitate the latter two species, we should perform additional morphological and karyological studies to verify the genetic nature of these species. Subcluster B includes F. pseudovina, F. rupicola, F. valesiaca, and F. musbelica. The STRUCTURE analysis revealed three genetic groups that did not correspond to the taxonomic classification. The PCoA revealed two well-defined genetic groups within F. valesiaca that differ in geographical distributions. The first one occurs in mountains (the Kurai ridge), while the second one grows on lowlands (the Priobskoe plateau). The third group is represented by F. rupicola specimens that differ from F. valesiaca by having leaf blades 0.5-0.8 versus (0.35)0.4-0.6 mm wide, lemma 3.8-4.5 versus (2.3)2.8-3.8 mm long, spikelets 5.5-7 versus (4)4.5-5.5(6) mm long, and 5-7 versus 5 vascular bundles. According to our analyses, individual 004342 identified by the keys (Alexeev, 1990;Lu et al., 2006;Tzvelev, 1976;Tzvelev & Probatova, 2019) as F. pseudovina, appeared to be of a hybrid nature between F. rupicola and F. valesiaca. Moreover, two individuals (004548 and 004549), identified as F. musbelica, also appeared to share genetic clusters represented by F. rupicola and F. valesiaca, although morphologically they have brown spikelets and leaf sheaths closed up to ⅓-⅟₄ of its length that are most specific for F. musbelica (Alexeev, 1990;Lu et al., 2006;Tzvelev, 1976;Tzvelev & Probatova, 2019). Additionally, six more specimens, preliminarily determined either as F. rupicola or F. valesiaca, also had a complex genetic pattern. Thus, our results support the prior research regarding hybridization in Festuca. We treat the current findings with caution due to the sample size being limited and we cannot deny the presence of incomplete lineage sorting and introgression that also may influence the complex genetic structure of these specimens.
Additionally, we detected a few specimens with a hybrid nature, for example, samples 004573 and 004550; however, morphologically, they correspond to the description of F. tschujensis. Festuca albifolia is also morphologically similar to F. tschujensis (Alexeev, 1990;Tzvelev, 1976;Tzvelev & Probatova, 2019). Nonetheless, our study demonstrates that a sample (1100006214) determined as F. albifolia appeared to be genetically closer to the F. kryloviana group that also includes specimens of F. borissii and F. kurtschumica. Festuca kryloviana exhibits high variability of morphological and anatomical characters that may depend on a different number of chromosomes (2n = 4x = 28 or 6x = 42; Chepinoga et al., 2010;Probatova & Sokolovskaya, 1980). Moreover, the result of the PCoA revealed that F. borissii is distinguished from F. kryloviana by the third axis. The ranges of these species overlap in the territory from the mountains of southern Kazakhstan to the northern part of the AMC. Morphologically, these species can be well-separated by the plant life form, the shape of the leaf blade crosssection, the lemma length, the awn length, and the length of the closed portions of the sheaths (Chusovlyanov & Kotukhov, 2006;Tzvelev & Probatova, 2019). In addition to the known species, STRUCTURE revealed an unknown genetic group found in F. albifolia, F. borissii, F. kryloviana, and F. kurtschumica. Possibly, this "ghost" cluster represents a species that is not included in the analysis. Alternatively, it may be inherited from an extinct species. In order to resolve the phylogenetic relationships within the Altai fescues, our further research should be supplemented with morphological and karyological studies due to different ploidy levels playing an important role in the description of the species. Importantly, we ought to enlarge the sample size of the studied taxa to verify if morphological plasticity is constant within their geographic ranges.

| CON CLUS IONS
In this study, we provide the first insight into the genetic structure within fine-leaved fescues of the AMC and a baseline for further investigations of the genus. Altai fescues were classified into five groups, two clusters and three subclusters, of closely related species. We found that Altai F. richardsonii is conspecific with F. rubra.
Festuca brachyphylla, F. brevissima, F. borissii, and F. saurica appear to be well-separated and genetically distinctive. Due to the usage of genome-wide genotyping, we were able to detect a complex genetic pattern in the F. valesiaca and F. kryloviana complexes. The inconsistency between morphological characters and molecular data for some species distributed within the Altai Mountains is the basis for evaluating the usefulness of the diagnostic characters currently being used to identify these species. We reckon that a combination of morphological, karyological, and molecular analyses is needed to resolve the remaining questions related to the interspecific relationships within the genus Festuca.

ACK N OWLED G M ENTS
We would like to express our gratitude to three anonymous reviewers for providing valuable comments on the manuscript as well as to the curators of ALTB, KRA, KUZ, LE, and TK for their assistance during visits and for providing a possibility of sampling for the research.
We are grateful to Prof. Pilar Catalán for her important suggestions and Ryzhakova D.D. for preparing the map.

FU N D I N G I N FO R M ATI O N
This study was supported by the Tomsk State University Development Programme (Priority-2030).

CO N FLI C T O F I NTE R E S T S TATE M E NT
None declared.